More Like this

1. Towards common ground in the biodiversity–disease debate

   https://doi.org/10.1038/s41559-019-1060-6  

   Rohr, Jason R.; Civitello, David J.; Halliday, Fletcher W.; Hudson, Peter J.; Lafferty, Kevin D.; Wood, Chelsea L.; Mordecai, Erin A. (January 2020, Nature Ecology & Evolution)
2. Panel: A Debate on Data and Algorithmic Ethics

   Stoyanovich, Julia; Howe, Bill; Jagadish, H.V.; Miklau, Gerome (January 2018, Proceedings of the VLDB Endowment)
3. Toward conciliation in the habitat fragmentation and biodiversity debate

   https://doi.org/10.1007/s10980-023-01708-9  

   Valente, Jonathon J.; Gannon, Dustin G.; Hightower, Jessica; Kim, Hankyu; Leimberger, Kara G.; Macedo, Rossana; Rousseau, Josée S.; Weldy, Matthew J.; Zitomer, Rachel A.; Fahrig, Lenore; et al (November 2023, Landscape Ecology)
4. Modeling the Factors of User Success in Online Debate

   https://doi.org/10.1145/3308558.3313676  

   Durmus, Esin; Cardie, Claire (January 2019, The World Wide Web Conference)

   Debate is a process that gives individuals the opportunity to express, and to be exposed to, diverging viewpoints on controversial issues; and the existence of online debating platforms makes it easier for individuals to participate in debates and obtain feedback on their debating skills. But understanding the factors that contribute to a user’s success in debate is complicated: while success depends, in part, on the characteristics of the language they employ, it is also important to account for the degree to which their beliefs and personal traits are compatible with that of the audience. Friendships and previous interactions among users on the platform may further influence success. In this work, we aim to better understand the mechanisms behind success in online debates. In particular, we study the relative effects of debaters’ language, their prior beliefs and personal traits, and their social interactions with other users. We find, perhaps surprisingly, that characteristics of users’ social interactions play the most important role in determining their success in debates although the best predictive performance is achieved by combining social interaction features with features 

   more » « less
5. The debate over understanding in AI’s large language models

   https://doi.org/10.1073/pnas.2215907120  

   Mitchell, Melanie; Krakauer, David C. (March 2023, Proceedings of the National Academy of Sciences)

   We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition. 

   more » « less